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In this chapter, we focus on the importance of establishing causal relationships in the organizational sciences. Specifically, we provide an explicit definition of a causal relationship, identify several different forms that have been explored in the scientific literature, and discuss the conditions under which causality can be established. Specifically, we discuss the Campbell Causal Model (CCM), which emphasizes threats to causal interpretations and the elimination of these threats, as well as the Rubin Causal Model (RCM), which emphasizes the biasing effect of non-random assignment of...

In this chapter, we focus on the importance of establishing causal relationships in the organizational sciences. Specifically, we provide an explicit definition of a causal relationship, identify several different forms that have been explored in the scientific literature, and discuss the conditions under which causality can be established. Specifically, we discuss the Campbell Causal Model (CCM), which emphasizes threats to causal interpretations and the elimination of these threats, as well as the Rubin Causal Model (RCM), which emphasizes the biasing effect of non-random assignment of participants to conditions (i.e., selection bias) and how to overcome this bias in observational research. A variety of quasi-experimentation designs (e.g., regression discontinuity approaches, longitudinal designs) that enable organizational science researchers to study phenomena in the field are discussed. We finish our chapter by considering the recent trend conceptualizing organizations as complex systems, and we argue that this perspective may change the kinds of causality questions that researchers ask in the future.